Survival outcomes for lung cancer, the leading cause of cancer-related mortality in the United States, remain poor. Improving lung cancer survival requires a multi-pronged approach, including smoking cessation and better elucidation of gene-environment interactions in risk, identification of new promising drug targets, as well as identification of potential prognostic and predictive markers that can help optimize treatment for patients. Our molecular epidemiology research group has investigated lung cancer risk and geneenvironment interactions in the first SPORE cycle,.and supported by R01 funding. Other proposed SPORE projects are directly addressing new potential targets for drug interventions. In SPORE Project 1, we will focus on identifying prognostic and predictive markers of survival in lung cancer. The ultimate goal of identifying such markers is to find ways to select the best treatment course for each patient. Recent studies by our group have demonstrated the importance of germline polymorphic variants as prognostic and predictive factors, but these studies have investigated only a few candidate polymorphisms relative to survival outcomes. In this SPORE renewal, we have adopted a high-density pathway approach to investigate more extensively and efficiently the role of entire pathways in survival outcomes. We selected pathways with biologic evidence for a role in tumor aggressiveness or treatment response. Although the eventual goal will be to evaluate germline DNA, serology, tumor-based tissue, and clinical factors in one cohesive model, at present we will focus on germline DNA to identify critical pathway markers. To achieve this goal, we will utilize a large'(n=1,000), mature NSCLC case series, early and late stages, with annotated DNA and clinical data to assess genetic variation in selected pathways as prognostic and predictive markers in NSCLC. In Aim 1 (gene discovery), we will use the Illumina Bead Station GoldenGate assay system for genotyping of single nucleotide polymorphisms (SNPs), which allows large-scale genotyping for up to 1,536 customized SNPs, to systematically assess the effects of genetic variation in these pathways on survival outcomes in 60% of our large sample size (discovery phase). For polymorphisms that cannot be assayed with this system and for candidate genes to be used in a validation phase (Aim 2) on the whole population, we will utilize other in-house techniques in the Genomics Core, including Sequenom and ABI 7900 Taqman. Though our primary endpoint will be overall survival (OS), we will also assess disease-free survival (DPS) and progression-free survival (PFS), where appropriate. Aims 3-4 will include assessing the role of gender and other factors in the genetic predictors of survival among lung cancer patients, using both stratified and interaction analyses;and assessing additional candidate genes (e.g. EGFR) and pathways identified from companion basic and translational science studies (Projects 2-5) in lung cancer outcomes. The detailed . clinical annotation of our case series is a unique resource with which to investigate prognostic and predictive markers, as well as for gene-environment interactions, in lung cancer survival.